Better, faster decisions
for everyone.
We’re the Context Factory trusted by frontier data teams.
From the team behind Uber’s Michelangelo AI platform.
The data team owns the factory.
It outputs answers trusted by CEOs.
The data team
Own the context. Skip the maintenance.
Delphina’s agents build, test, and maintain your context. You set direction and approve changes.
Everyone, up to the CEO
Ask directly. Get answers you can act on.
Ask in plain language for an answer, a research report, or a data app. All grounded in context your data team owns.
Loved by CDOs and CEOs.
“We’re an airline that thinks of ourselves as a tech company. Delphina is a core part of how we’re delivering on that.”
Andrés Bucchi
CDO & Chief Engineering Officer
“10 years in this business, and I’m still finding new insights every day through Delphina.”
Waleed Nasr
CEO
“I stopped waiting for reports and started finding answers myself.”
Zach Gordon
Co-CEO
“Delphina gives us AI superpowers for data. It’s changed how we make decisions.”
Chris Best
CEO
The factory comes online in a day.
Agents read your sources, build the context, and test it against your dashboards.
You approve, and it’s live.
Context from your sources
Read from dbt, dashboards, docs, and query logs, and kept current as they change. Nothing is migrated.
Evals from your dashboards
Tests from trusted dashboards and approved corrections guard what your team has already verified.
Fixes land in your knowledge base
Agents draft changes for your team to approve. Definitions land versioned, with regression tests.
Fast to deploy. Faster to trust and scale.
Accuracy compounds with use.
Agents find and fix the gaps. Your team approves every change.
- Search dbt, Looker, Notion · no definition found
- Expert graph → Priya Nair, owner of fct_orders
- Ask Priya in #data-help→ Slack · #data-help · 9:46 am@Priya quick one from a question Maya asked in Delphina: how do we define a reactivated customer? Two mentions in Notion, no definition, and you own fct_orders.
- Priya answers · fact approved✓ Published to knowledge base · 9:52 amReactivated customer — a customer who places an order after 90+ days without one. Free-trial accounts excluded.v1 · Priya Nair · approved in Slack
- Re-run Maya’s question · answer changed
- Save as a regression test
- Close · notify Maya
fct_orders.
Context projects lag and decay.
The factory fixes both.
Context layers have the same problems as semantic layers.
- They lag. Model first. Learn what matters later.
- They decay. The business moves. The definitions don’t.
- AI writes the wrong thing faster. Still a guess. Still decays.
Delphina’s Context Factory fixes this by following real demand.
- Start from evidence. Query logs, dashboards, and dbt models.
- Follow demand. Every question shows what matters now.
- Agents do the work. Draft, test, ship. Your engineers approve.
Ask a question. Or build an app.
Both in plain language. Delphina does the rest.
Chat
Ask. Get an answer you can act on.
Ask in plain language. Delphina answers from the context the factory built, pulling data from your warehouses and MCP servers, with the chart, the table, and the SQL behind it.
See the chat →
Data apps
Build. From a prompt to a data app.
Describe the dashboard or tool you need. Delphina builds it on the same factory context, pulling from the same warehouses and MCP servers, as a refreshable app you can edit, publish, and embed.
See data apps →
Your data and your context.
Your side of the boundary. Always.
Delphina works with every frontier model and belongs to none of them. Your context is portable, your data stays put.
Coding agents belong on laptops.
Sensitive company data doesn’t.
Direct data access
Data & context land on the laptop and stay there.
Hard to track, harder to clean up, and easy to leak.
With Delphina
Data & context stay protected in the governed data plane.
Only answers come back to the browser or coding agent.
Type II Certified
Annual audit. Continuous controls monitoring. Report available under NDA.
Read-only, least-privilege
Delphina connects with per-user read-only credentials. It sees only the tables you grant.
Single-tenant data plane
Every customer gets a separate, isolated data plane.
Isolated execution
Python and DuckDB run in an isolated Firecracker microVM with no internet access.
Structured logs
Every prompt, query, and knowledge reference logged and exportable.
Meet Delphina.
Context Factory for the data team. Better, faster decisions for everyone. Live in days.